A Personalized Tag-Based Recommendation in Social Web Systems

Autor:	Durao, F., Peter Dolog
Rok vydání:	2012
Předmět:	recommendation Social and Information Networks (cs.SI) FOS: Computer and information sciences tag Computer Science - Social and Information Networks personalization Information Retrieval (cs.IR) Computer Science - Information Retrieval
Zdroj:	Durao, F & Dolog, P 2009, ' A Personalized Tag-Based Recommendation in Social Web Systems ', CEUR Workshop Proceedings, vol. 485, pp. 40-49 . < http://ailab.dimi.uniud.it/en/events/2009/ap-web20/proceedings/papers/paper5-F.pdf > Scopus-Elsevier
DOI:	10.48550/arxiv.1203.0332
Popis:	Tagging activity has been recently identified as a potential source of knowledge about personal interests, preferences, goals, and other attributes known from user models. Tags themselves can be therefore used for finding personalized recommendations of items. In this paper, we present a tag-based recommender system which suggests similar Web pages based on the similarity of their tags from a Web 2.0 tagging application. The proposed approach extends the basic similarity calculus with external factors such as tag popularity, tag representativeness and the affinity between user and tag. In order to study and evaluate the recommender system, we have conducted an experiment involving 38 people from 12 countries using data from Del.icio.us, a social bookmarking web system on which users can share their personal bookmarks
Databáze:	OpenAIRE
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